Explore: Nonlinear Regression

statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination

In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable

regression; a model with two or more explanatory variables is a multiple linear regression. This term is distinct from multivariate linear regression

called regressors, predictors, covariates, explanatory variables or features). The most common form of regression analysis is linear regression, in which

Local regression or local polynomial regression, also known as moving regression, is a generalization of the moving average and polynomial regression. Its

the probit regression, (ii) threshold regression, (iii) smooth regression, (iv) logistic link regression, (v) Box–Cox transformed regressors ( m ( x ,

Linear and Nonlinear Regression: A Practical Guide to Curve Fitting. Oxford University Press. ISBN 978-0-19-803834-4.[page needed] Regression Analysis By

In statistics, ordinal regression, also called ordinal classification, is a type of regression analysis used for predicting an ordinal variable, i.e.

Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes

In statistics, regression toward the mean (also called regression to the mean, reversion to the mean, and reversion to mediocrity) is the phenomenon where